Artificial Intelligence (AI): A Catalyst for Active Management
Dear Fellow Investors,
I hope this letter finds you all well and enjoying your summer. At risk of you already feeling inundated with, and perhaps tired of, the Artificial Intelligence (AI) conversation, I wanted to share a few thoughts on how we at Grandeur Peak are thinking about it. This is not a primer on AI – if you want that I am sure you have all figured out by now that you can just ask ChatGPT what the different types of AI are or how AI is being utilized today across various industries, etc.
Instead, I want to share in general terms how we are considering the AI impact on our portfolio decisions and prepared to use AI in our investment process. Within Grandeur Peak there are wide-ranging perspectives on the importance of AI and various levels of expectations for where its capabilities are going. This makes for great debate. What I can tell you is that from a CIO and executive management perspective, we are taking it very seriously. AI is real and it is a big deal – it is already touching all our lives and its impact will reach further and further as months and years pass. Many companies say that AI is not new and that they have been using it for years. While this is true, it is now available for the world to see, and its rapid pace of advancement is opening new possibilities every day. Technological advancement always brings threats, and it brings opportunities – Artificial Intelligence is certainly no different, and quite possibly distinctively disruptive.
All of us have seen the obvious and most advertised AI winners (e.g., Nvidia Corporation (NVDA) – up +190% year-to-date through June) and losers (e.g., Chegg, Inc. (CHGG) – down -65% year-to-date through June) – but I believe that we are just entering what will be a prolonged period of opportunity for active management. We are already observing the beginnings of this. Threats and Opportunities abound. The market is chasing Nvidia higher nearly every day, and perhaps correctly, due to its GPU (Graphics Processing Units) technology, originally applied to the video game space, but also adept at running multiple concurrent processes – a feature well positioned in the competitive AI landscape. New GPU technologies will emerge (opportunity), as existing competitors and new entrants may develop new competitive technologies with better performance and increased efficiency at lower costs (opportunity). Nvidia will likely look to acquire some of these potential threats but that is beside the point.
The point is that all these GPU companies need components, suppliers, testing, etc. that are provided by little companies all over the world (opportunity). But GPUs are not the only way to play Artificial Intelligence. AI is an accelerant to a theme we have been focused on for years – data, automation, and proliferation of technology generally. All this data being generated needs to be collected, cleaned, analyzed, visualized, modeled, integrated, stored, governed, and protected. More software. More semiconductors. More hardware. Opportunity, opportunity, opportunity.
For better or for worse, the impact of AI will be far reaching. We have all had conversations with friends and family about whose jobs are most at risk – the lawyer or the software engineer or the….analyst? Grandeur Peak has always been heavily invested in human capital services businesses and so some of our companies have been caught in the crosshairs of this uncertainty. In some cases, deservedly so, and in others it is likely to be proven unsubstantiated fear. That is part of the reason we have been so acutely focused on the current and potential impact of AI.
Looking at the markets this year, many investors have taken the approach of selling (or buying in the case of NVDA and a few other mega cap tech stocks) and asking questions later, and the push in Technology names has certainly been a performance headwind for us as a result thus far. Just as opportunity abounds, the threat is also real.
As active managers, we have thoughtfully and methodically gone thru each of our companies. In several instances, we have found reasons to either exit/reduce positions or add/increase positions. The uncertainty is not going to just rapidly dissipate. This exercise will be ongoing and relevant for years to come. Some companies’ existence will be called in to question. Many will be impaired and need to adapt their business and revenue models while others will acclimate more seamlessly. Some will have the wind at their backs and there will be many high-quality companies that innovate and leverage new technology better than peers. It is a uniquely stressful time given so many companies (including great companies we have known and loved for years) are at risk of being compromised. If I were to create a bell curve representing the future financial impact of AI on businesses, I think it would be somewhat evenly distributed with fat tails, meaning a higher number of companies will be more significantly impacted by AI than a normally distributed curve might suggest. While it is a stressful time, it is an equally exciting time as we seek to determine where each company falls on this distribution. With massive threats and opportunities, winners and losers are already emerging. But we are still in the early days.
We believe our team structure, industry specific expertise, and global perspective favorably position us to identify these threats and opportunities as they emerge. AI impact is not isolated to Technology companies and is certainly not exclusively a US phenomenon. The impact will be seen across industries and geographies. We believe there is a great opportunity for our various teams to work together and connect inter-industry global dots.
We are leaning heavily into our relationships with our portfolio companies as we strive to explore, in great depth, these threats and opportunities. We are talking with competitors of our companies to see how strategies differ, attending conferences, and engaging with industry experts. To gain more insight into AI, we are interviewing AI specialists and using hands-on AI tools. We are also incorporating all our learnings in our quality scores for each company. A big part of our quality scoring has always been centered on competitive positioning – we are now studying AI-related risks and opportunities as part of our diligence and expressing those in our rating framework.
To my earlier point, AI is not new. Various forms of it have been in use for years now. But capabilities are improving, and new use cases are constantly emerging. This not only applies to companies we evaluate but to our own company. For years now, the Grandeur Peak team has been generating, capturing, and storing unique data. For example, we have generated data from each of our company interactions and subsequent conclusions and recommendations from each of those touch points. We have performed detailed QVM (quality/value/momentum) analysis and scored thousands of companies. We have always known that all this data would be beneficial to us as we try to learn from the past to improve future decisions. Questions we can ask ourselves and reasonable expect to generate an answer are as follows:
- What combination of QVM scores yields the best results?
- What company attributes are most predictive of stock performance?
- What combinations of company attributes are most predictive?
- What are the commonalities across our largest detractors over our history?
- What are the errors that each of our analysts make and repeat?
The list of questions we can ask and learn from are endless. We have often talked about one of Warren Buffett’s famous quotes, “We don’t have to be smarter than the rest. We have to be more disciplined than the rest.” That is why we have been so insistent on capturing this data from every company and every company touch from our inception 12 years ago. It turns out that all this data I have mentioned, among other sources of unique data we are capturing, is a solid foundation for data-training. We always knew our data could be leveraged into improved decision making, but we now live in a world where those insights come faster and more comprehensively than we could have imagined.
Over the last several years, we have made significant investments in infrastructure, people, technical skills, and data with an aim to improve the capabilities of our quantitative research team. These investments also position us to take advantage of advances in AI and Machine Learning (ML). We have migrated all our data to the cloud to improve both the scale and the speed of our processes. We have built incredible tools, data collection, and automation into our processes. We now have a centralized ‘Research Toolkit’ that streamlines our research process and workflow.
We have segmented our transactional and analytical databases and organized, cleaned, and migrated our proprietary data to stronger platforms. We are proud of our quantitative research team and what they have accomplished over the last couple of years. They collectively have expertise in math, computer science, and programming in addition to their deep understanding of finance, and the Grandeur Peak process. They are the definition of a team and deserve recognition for the work they are doing that is so critical to our process and to the buildout and implementation of any future AI development. I should also mention our Chief Technology Officer, John Parker, who is a sounding board and ensures our quantitative research team has the tools and security needed execute on our vision.
In all my study of AI, one thing has become abundantly clear – AI is not a silver bullet – not for the companies we research, nor the companies we invest in, and certainly not for Grandeur Peak’s research process. We do not anticipate that we would ever fully automate the Grandeur Peak process or get to a place where machines are making our portfolio decisions. However, we recognize that the world is changing rapidly and that machines have some capabilities and scalability that go beyond human reach.
Our goal has always been to be a learning organization and try to get better every day. We always have and always will invest in people and tools and explore various ways to enhance and augment our process. AI is another tool for us – we still do not know for certain just how much better it can make us, but we will explore every avenue to ensure we optimize our portfolio decision making. We could sit idly and do things as we always have and ignore that the world is changing (threat). Instead, we are exploring, investing, and embracing AI to learn, grow and improve (opportunity).
Randy Pearce, CFA
Chief Investment Officer
Grandeur Peak Global Advisors
The objective of all the Grandeur Peak Funds is long-term growth of capital.
An investor should consider investment objectives, risks, charges, and expenses carefully before investing. To obtain a prospectus, containing this and other information, visit www.grandeurpeakglobal.com or call 1-855-377-PEAK (7325). Please read it carefully before investing.
Mutual fund investing involves risks and loss of principal is possible. Diversification does not eliminate the risk of experiencing investment loss. Investing in small-cap funds will be more volatile and loss of principal could be greater than investing in large cap or more diversified funds.
Investing in foreign securities entails special risks, such as currency fluctuations and political uncertainties, which are described in more detail in the prospectus. Investments in emerging markets are subject to the same risks as other foreign securities and may be subject to greater risks than investments in foreign countries with more established economies and securities markets.
 As of 7/31/23, the Grandeur Peak Funds own zero shares of Nvidia Corporation (NVDA US), and zero shares of Chegg, Inc. (CHGG US)